When you hear concepts over and over, you often wonder is it because it’s swarming or because your ear is newly attuned to it? Did you know there’s a lot of people who believe that the #11 has super powers and that’s why when they look at the clock, it’s always 11 after? Seriously.
UX is hip. And rightly so. I thought I’d share a theory why this is so and what impact it might have on your startup. This despite the fact that I’m relatively new to UX concepts.
As an early believer in Lean Startup movement, I can perhaps be excused for my unbridled enthusiasm for the release of Eric Ries’ new book, The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses. Not however, for the reasons you might expect.
In fact, some early adopters of Lean Startups — those who have already bought into the framework to the extent that they’ve applied its practices into their high tech startup — might be a tad disappointed. They might have to look a little deeper; there’s no vanity steps to success herein.
During the next week of reflection, a non-early adopter, but loyal user of the product called the founder to announce that he would not after all, pay for the product. Not at the proposed price, not at the price they had argued for, not at any price.
So he fired himself as Founder and CEO of his company. And then he fired me. (“I no longer need your services. But in the future…”)
We talked briefly about his future, including possible pivots and leaps, but essentially, the gig was up. I admire his self-awareness and the honesty with which he evaluated his situation.
Whether there’s a tech bubble or not is an interesting discussion going on in the blogosphere. (Reading guide is below.)
I fall into the “boom before bubble” pack. Having lived through the 90s’ bubble, there’s no way we’re there yet. That doesn’t mean there won’t be one, but my feeling is we’re skating a razor’s edge off one side of which looms another wave of housing foreclosures and a doom & gloom Sequoia presentation. Investors herding like sheep around darling Silicon Valley startup memes is not in itself bubblicious, it’s SOP. Sheep investing affects supply and demand conditions that result in higher valuations. Good or bad, that doesn’t in itself represent a bubble.
The Internet bubble was about more that overvalued startups. Horowitz and Graham argue other dynamics way better than I can (see links below), but I think it’s important to point out that bubbles dramatically affect the entire economic climate. The bubble was “our” version of 70s inflation. The bubble caused a huge migration of people to the SF Bay Area. Salaries went through the roof (not just for engineering talent.) So did cost of living. In the 90s, the housing bubble was inseparable from the Internet bubble. The buying of lots of different goods became irrational.
Despite Dave McClure’s imploring to “kill a feature” and Eric Ries’ urging to “cut your product in half, then halve it again,” most startup founders I encounter are trying to work their way toward Product-Market fit by planning and building new features. The analytical mind of an entrepreneur, both engineer and business-side, naturally tends toward solving problems and ostensibly, features solve problems. But it’s the wrong approach for most startups.
The Innovator’s Dilemma not only forms the foundation of Lean Startups and Customer Development, but has brilliant analysis on the role of disruptive vs sustaining innovation in large successful businesses. In a nutshell, big successful companies successfully adopt sustaining technologies that maintain a steady trajectory of performance/cost improvements. These same companies, however, fail to adopt disruptive technologies that radically change performance/cost trajectories. The success of the former dictates the level of success of that business as long as the adopted trajectory is dominant in the marketplace. These businesses tend naturally to move “up market” to maintain or increase margins as the (IMO) traverse into late majority adoption in the technology adoption curve. If and when, however, the disruptive trajectories become dominant (for whatever reason) these same businesses fail, because they are unable to respond to the startups eating up their core business.
